Triple
T6807593
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Diane |
E156346
|
entity |
| Predicate | etymologicalRoot |
P453
|
FINISHED |
| Object | Latin "Diana" |
E71669
|
NE FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Latin "Diana" | Statement: [Diane, etymologicalRoot, Latin "Diana"]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Latin "Diana" Context triple: [Diane, etymologicalRoot, Latin "Diana"]
-
A.
goddess Roma
Goddess Roma is the personification of the city and state of Rome, venerated in Roman religion as a divine embodiment of Roman power, identity, and eternity.
-
B.
Romana
Romana is a highly intelligent and compassionate Time Lady from the Doctor Who universe who serves as one of the Doctor’s most capable and scholarly companions.
-
C.
Romana
Romana is a small municipality in the Logudoro region of Sardinia, Italy, known for its rural landscape and traditional Sardinian character.
-
D.
Diana
Diana is a renowned sculpture by Brazilian-Italian modernist artist Victor Brecheret, exemplifying his stylized, classical approach to the human figure.
-
E.
Diana
chosen
Diana is a feminine given name of Latin origin, famously borne by the Roman goddess of the hunt and by Diana, Princess of Wales.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69c68826e6a48190a3d220b541e639de |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d30a006081908996e31aa7ced0ac |
completed | March 27, 2026, 6:57 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c71aa27cec81909f45911ffa44ea6f |
completed | March 28, 2026, 12:02 a.m. |
Created at: March 27, 2026, 2:16 p.m.